Toward a holistic understanding of performance in Lean Manufacturing: a discussion on the relevance of its indicators

Abstract

Purpose This study aims to propose a novel approach to select and prioritize performance indicators in Lean Manufacturing depending on whether they are influencing or being influenced by others, thereby assisting in the decision-making process for improving overall performance. Design/methodology/approach The methodology comprises two stages. First, a literature review was conducted to identify the performance indicators, and then their interrelationships were analyzed by means of the decision-making trial and evaluation laboratory (DEMATEL) multi-criteria decision-making (MCDM) method. Findings The results provide a comprehensive visualization of the performance indicators in Lean Manufacturing, with a total of 50 identified indicators. Among these, 29 were categorized as causal, meaning that their results mainly influence the others, and 21 as influenced, with their results mostly being influenced by others. Among the causal indicators, those related to the human factor (eight indicators) were the most predominant. However, the most-cited performance families in the literature do not stand out as being causal, but rather as mostly influenced. Practical implications This study can help managers improve and analyze performance more effectively, while focusing on the importance of choosing causal over influenced indicators. Originality/value Performance measurement plays a crucial role for organizations, but because of the increasing number of metrics, there lacks an established framework. This exploratory study thus opens the discussion on relevance to determine a group of coherent and connected indicators that could help measure performance in a more comprehensive manner, rather than in several isolated parts.